To introduce the above behavior to the decision-making of CAVs, we seek to develop a model that generalizes the incentive criterion proposed in Equation (REF ).
To include the long-horizon criterion, we introduce an acceleration gain component based on the event dynamics. Downstream acceleration gains are computed with respect to virtual “vehicles” placed at the incident tail
(Figure REF ). The
states
of these
vehicles are assigned based on
the incident tail, and provided to a car-following model
\(f(\cdot )\)  as in [1]} to compute
accelerations:
\(a_{d} = f(h_{d}, v_\alpha , v_{\text{avg},o}), \ \ \ \tilde{a}_{d} = f(h_{d}, v_\alpha , v_{\text{avg},n})\) 
